Parameter Estimation of Gamma-Gamma Fading with Generalized Pointing Errors in FSO Systems

In this paper, the challenges of parameter estimation for the Gamma-Gamma turbulence channels with generalized pointing errors are addressed. The Kolmogorov-Smirnov goodness-of-fit statistical test results indicate that the approximate probability density function obtained by the saddlepoint approximation (SAP) method provides a better approximation for a larger value w z , and this means that the proposed method is more efficient for the FSO links over long distances when the transmit divergence angle at the transmitter side is fixed. Also, an additional parameter k needs to be estimated in addition to the shaping parameters α and β under the SAP method. An estimation scheme for the shaping parameters is proposed based on the SAP method. The performance of the proposed estimation is investigated by using the mean square error (MSE) and normalized mean square error (NMSE). The results indicate the proposed estimator exhibits satisfactory performance in both noiseless and noisy environments. The effects of the receiver aperture on the estimation performance are also discussed.

Incorporating family disease history and controlling case-control imbalance for population based genetic association studies

In the genome-wide association analysis of population-based biobanks, most diseases have low prevalence, which results in low detection power. One approach to tackle the problem is using family disease history, yet existing methods are unable to address type I error inflation induced by increased correlation of phenotypes among closely related samples, as well as unbalanced phenotypic distribution. We propose a new method for genetic association test with family disease history, TAPE (mixed-model-based Test with Adjusted Phenotype and Empirical saddlepoint approximation), which controls for increased phenotype correlation by adopting a two-variance-component mixed model and accounts for case-control imbalance by using empirical saddlepoint approximation. We show through simulation studies and analysis of UK-Biobank data of white British samples and KoGES data of Korean samples that the proposed method is computationally efficient and gains greater power for detection of variant-phenotype associations than common GWAS with binary traits while yielding better calibration compared to existing methods.

Improved Method for Approximating the Hazard Rate for Convolution Poisson Random Variables

In this study, we investigate the performance of the saddlepoint approximation of the probability mass function and the cumulative distribution function for the weighted sum of independent Poisson random variables. The goal is to approximate the hazard rate function for this complicated model. The better performance of this method is shown by numerical simulations and comparison with a performance of other approximation methods.

An efficient and accurate frailty model approach for genome-wide survival association analysis controlling for population structure and relatedness in large-scale biobanks

With decades of electronic health records linked to genetic data, large biobanks provide unprecedented opportunities for systematically understanding the genetics of the natural history of complex diseases. Genome-wide survival association analysis can identify genetic variants associated with ages of onset, disease progression and lifespan. We developed an efficient and accurate frailty (random effects) model approach for genome-wide survival association analysis of censored time-to-event (TTE) phenotypes in large biobanks by accounting for both population structure and relatedness. Our method utilizes state-of-the-art optimization strategies to reduce the computational cost. The saddlepoint approximation is used to allow for analysis of heavily censored phenotypes (>90%) and low frequency variants (down to minor allele count 20). We demonstrated the performance of our method through extensive simulation studies and analysis of five TTE phenotypes, including lifespan, with heavy censoring rates (90.9% to 99.8%) on ~400,000 UK Biobank participants with white British ancestry and ~180,000 samples in FinnGen, respectively. We further performed genome-wide association analysis for 871 TTE phenotypes in UK Biobank and presented the genome-wide scale phenome-wide association (PheWAS) results with the PheWeb browser.